Awareness of caregivers of geriatric deficits among older people—the results of a cross-sectional study in Krakow, Poland
Bibliographic record
Abstract
BACKGROUND: It seems that caregivers (CGs) may be a reliable source of information for determining health condition of seniors. This might be important for general practitioners (GPs) and facilitate them conducting comprehensive geriatric assessment (CGA). The objectives of our study were to: compare populations of older patients with and without CGs, characterise the group of CGs, establish whether CGs are aware of patients' deficiencies in areas of CGA. METHODS: Patients aged at least 65 years underwent CGA using eight tools in GPs' practices in and around Krakow, Poland. Seniors were divided into two groups: with and without CGs. CGs filled in an authors' questionnaire on their data and assessed seniors in eight domains corresponding to the tests used in CGA. Patients with and without CGs were also compared in terms of CGA results and basic demographic and medical data. Subjective CGs' responses were compared with objective CGA results. RESULTS: We conducted CGA on 438 senior patients. Two hundred fifty eight (59%) of them were classified as patients with CGs. Patients with CGs were older, less educated, more often lived in rural areas and were more frequently in a relationship (as all p < 0.05). In seniors with CGs, the results of frailty (p < 0.008) and insomnia scales (p = 0.049) were significantly worse. Mostly, CGs could properly assess seniors in basic and complex living activities and nutritional status. They were less precise in determining deficits like depressive tendency and insomnia. CONCLUSIONS: CGs' assessment of older patients can be a valuable source of information about seniors and can be helpful in diagnosing important health issues. CGs have difficulties when asked to properly assess depression and insomnia in the older adults they care for and their answers do not always correspond with the results of CGA. GPs should pay more attention to the needs of CGs themselves and provide them with the necessary knowledge about caring for older people.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".